resolved: looped returns

yolov5.py

@@ -133,7 +133,7 @@ class DeepFeatureFactorization:
                  model: torch.nn.Module,
                  n_components: int = 16):
         if isinstance(input_tensor, np.ndarray):
-            input_tensor = torch.from_numpy(input_tensor)  # Convert NumPy array 
+            input_tensor = torch.from_numpy(input_tensor) 
 
         batch_size, channels, h, w = input_tensor.size()
         _ = self.activations_and_grads(input_tensor)
@@ -234,8 +234,7 @@ def dff_nmf(image, target_lyr, n_components):
         image_array = np.array(fig.canvas.renderer.buffer_rgba())  # Convert to numpy array
         results.append(image_array)
         plt.clf()  
-
-        return image_array
+        #return image_array
 
 
     return rgb_img_float, batch_explanations, results